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Background: Understanding cancer symptom cluster through network analyses is a new approach in oncology, revealing interconnected and influential relationships among reported symptoms. We aimed to assess these relationships using network analysis in posttreatment breast cancer patients, focusing on the five dimensions of cancer‐related fatigue (CRF), and on other common difficulties encountered by oncological patients (i.e., pain, anxiety, depression, sleep difficulties, cognitive impairments, and emotion regulation and mental adaptation difficulties). Method: This study involved a complementary analysis of data from two interventional studies. Participants completed questionnaires before and after the intervention, with baseline scores being used in this article. Partial correlation network analysis modeled the relationships between symptoms in five distinct networks, each of them including one specific dimension of CRF. The core symptom in each network was identified based on the highest centrality indices. Results: Depression emerged as the core symptom in all networks, strongly associated with all fatigue dimensions (partial correlations ranging from 0.183 to 0.269) except mental fatigue. These findings indicate robust connections between symptoms, as variations in depression scores directly or indirectly influence fatigue and other symptoms within the cluster. Conclusion: Our results support the multidimensional aspect of CRF, and its links with other common symptoms. To effectively reduce patient CRF, interventions should address not only fatigue but also the closely related symptoms from the cluster, such as depression, given its centrality in the cluster. Trial Registration:ClinicalTrials.gov (NCT03144154 and NCT04873661). Retrospectively registered on May 1, 2017 and April 29, 2021, respectively. [ABSTRACT FROM AUTHOR]

Irritable bowel syndrome (IBS) is a prevalent chronic functional gastrointestinal disorder, characterised by recurrent abdominal discomfort and altered bowel movements. IBS cause a significantly negative impact on quality of life (QoL). Growing pharmacological evidence suggests that berberine (BBR) and curcumin (CUR) may mitigate IBS symptoms through multiple complementary synergistic mechanisms, resulting in the attenuation of intestinal inflammation and regulation of bowel motility and gut functions. In the present observational study conducted under real-life routine clinical practice settings, 146 patients diagnosed with IBS were enrolled by general practitioner clinics and pharmacies in Belgium. For the first time, this study assessed the potential synergistic pharmacological effect of a combined oral BBR/CUR supplement (Enterofytol® PLUS, containing 200 mg BBR and 49 mg CUR) (two tablets daily for 2 months), serving as complementary therapy in the management of IBS. Following the 2-month supplementation, significant improvements were observed in the patients' IBS severity index (IBSSI) (47.5%) and all the primary IBS symptoms, such as abdominal discomfort (47.2%), distension (48.0%), intestinal transit (46.8%), and QoL (48.1%) (all p < 0.0001). The improvement in the patients' IBSSI was independent of age, sex, and IBS sub-types. The patients' weekly maximum stool passage frequency decreased significantly (p < 0.0001), and the stool status normalized (p < 0.0001). The patients' need for concomitant conventional IBS treatment decreased notably: antispasmodics by 64.0% and antidiarrhoeals by 64.6%. Minor adverse effects were reported by a small proportion (7.1%) of patients, mostly gastrointestinal. The majority (93.1%) experienced symptom improvement or resolution, with a high satisfaction rate (82.6%) and willingness to continue the supplementation (79.0%). These findings support the potential synergistic pharmacological role of BBR and CUR in IBS, and their co-supplementation may alleviate IBS symptoms and improve QoL. [ABSTRACT FROM AUTHOR]

The amount of data collected from patients involved in clinical trials is continuously growing. All baseline patient characteristics are potential covariates that could be used to improve clinical trial analysis and power. However, the limited number of patients in phases I and II studies restricts the possible number of covariates included in the analyses. In this paper, we investigate the cost/benefit ratio of including covariates in the analysis of clinical trials with a continuous outcome. Within this context, we address the long-running question "What is the optimum number of covariates to include in a clinical trial?" To further improve the benefit/cost ratio of covariates, historical data can be leveraged to pre-specify the covariate weights, which can be viewed as the definition of a new composite covariate. Here we analyze the use of a composite covariate to improve the estimated treatment effect in small clinical trials. A composite covariate limits the loss of degrees of freedom and the risk of overfitting. [ABSTRACT FROM AUTHOR]